The recent explosion in popularity of e-commerce has contributed to increased volatility of

demand in parcel logistics chains, giving rise to the conflict between the rigidity of the

physical and human resources and unpredictable volumes of parcels generated by consumers'

orders. While there is a considerable body of research dedicated to last-mile logistics from a

strategic point of view, surprisingly little research has focused on the impact of this

phenomenon on the operations of the people involved. This paper explores how demand

volatility affects the operational activities of parcel service companies, focusing on how

volume variations affect route planning and capacity use, what problems emerge when

dealing with high and low demands, what adjustment methods are used, and whether they

lead to solving the initial problem or to secondary issues.

This paper employs qualitative design of case studies based on semi-structured interviews

with operational managers, terminal workers, coordinators, and drivers of five parcel delivery

organizations – UPS, Airmee, Bring, Bonway and PostNord – in Sweden, including

representatives from different organizational levels, from drivers to area managers. Thematic

analysis with six pre-established themes was performed to analyze the results.

As a result, it was found that demand volatility occurs systematically and depends on the

peculiarities of each organization, following company-specific weekly and seasonal patterns

caused mainly by e-commerce. High volumes pose capacity constraints for sorting

operations, human resources, and transportation vehicles, while low volumes pose idle cost

concerns due to similar constraints. The coping strategies include flexible scheduling,

real-time route adjustment, and managing capacity outside the organization; however, all of

them have their own secondary costs. Information asymmetry, uncertainty associated with

upstream supply chain dynamics, and lack of real-time destination information emerged as

the reasons why all organizations struggled to implement plans in practice. Overall, the main

finding was that demand volatility was handled but not solved, with experiential judgment

playing an essential role alongside technologies-based forecasting techniques.